Introduction: Structural variants (SVs) are a unique class of mutations which have certain therapeutic implications for the tumor. Certain SVs, such as chromosomal aneuploidy, whole-genome doubling (WGD), have specific therapeutic implications. The underlying cellular processes present in the tumor are reflected in mutational signatures. Here, we describe the landscape of chromosomal aneuploidy, WGD and mutational signatures in the National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR) to facilitate the investigation of their roles in therapeutic responses of the preclinical models. Method: Chromosome arm-level aneuploidy was called by scoring at the individual arm level if >90% of the arm copy number (CN) was gained/lost based on whole-exome sequencing (WES) data. Aneuploidy score was defined as number of arms with aneuploidy. WGD was determined by derived allelic specific CN, purity and ploidy from tumor/normal matched samples and permutation test. Mutational signatures (COSMIC v3) including single base substitutions (SBS), doublet base substitutions (DBS), small insertions and deletions (ID) and CN signatures were derived using SigProfiler for specimens with somatic mutations and CNs. Results: A large fraction (85%) of patient-derived xenograft (PDX) models (N=755) have at least one arm -level aneuploidy. Certain chromosomes and arms (7, 8, 17p and 18) are more frequently aneuploid, which might be biased due to the overrepresentation of gastrointestinal cancer in the cohort. Histology specific differences were observed in the frequency of arm level aneuploidies. For example, synovial sarcoma (SYNS) and endometrioid carcinoma (UEC) have much lower level of aneuploidy than non-small cell lung cancer (NSCLC) or clear cell renal carcinoma (ccRCC) models. 61% of PDX models (N=277) have WGD, in which certain histologies have more WGD [NSCLC: 81%, head and neck squamous cell carcinomas (HNSCC): 71%] than others. Samples having WGD have a higher degree of aneuploidy and chromosomal instability. WGD and aneuploidy remain stable along the passages in 78% PDX models. Intra-model heterogeneity of WGD was observed due to lineage difference. Mutational signatures (SBS6,15,20) indicating concurrent DNA polymerase epsilon (POLE) mutation and defective DNA mismatch repair were highly enriched in microsatellite instability-high models (p<0.01, Fisher’s exact test). Among 30 PDX models where the patients had known platinum-based chemotherapy history, 40% of them had an identifiable platinum chemotherapy treatment signature (SBS31 or DBS5). Chromothripsis associated amplification signature (CN8) was enriched in models with WGD (p<0.05). Conclusion: We have characterized chromosomal aneuploidy, WGD and mutational signatures in NCI PDMR models. The models with SVs can be utilized in preclinical drug studies to understand their role in therapeutic response in patients. Citation Format: Li Chen, Biswajit Das, Ting-Chia Chang, Yvonne A. Evrard, Chris A. Karlovich, Alyssa Chapman, Brandie Fullmer, Ashley Hayes, Ruth Thornton, Nikitha Nair, Shahanawaz Jiwani, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Corinne Camalier, John Carter, Suzanne Borgel, Tiffanie Miner, Chelsea McGlynn, Justine Mills, Shannon Uzelac, Tia Shearer, Lauren Hicks, Michelle Norris, Carley Border, Sergio Alcoser, Thomas Walsh, Michael Mullendore, Michelle Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Chromosomal aneuploidy, whole-genome doubling and mutational signatures in NCI PDMR models. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6072.

Background: Breast cancer is the second most common cancer in women. In 2022, it accounted for 15% of total new cancer cases and is the number four cause of death among all cancer types. To benefit from precision medicine, distinguishing molecular subtypes for prognosis and treatment in a clinical setting is essential. While intrinsic subtype classification from NGS results of patients is well established, the approach has not been comprehensively described for patient-derived xenograft (PDX) models, which have been shown to be powerful in translational research. The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) provides rich information in developing the method. Materials and Methods: Normalized gene expression data of breast cancer PDX and patient specimens (originators) were extracted using tximport and DESeq2 based on RNA-seq analysis. The immunohistochemistry (IHC) was used to determine the status of ER, PR and HER2 receptor expression in these tumor specimens. The PAM50 classification was performed by the R package Genefu. For further analysis, the PAM50 centroids for all 5 subtypes were also obtained from Genefu. Results: Using the RNA-seq data from 43 PDX models (180 PDX samples, 4~6 samples/model), we were able to predict subtypes at the model level based on the PAM50 method: There are 1 Luminal A subtypes, 5 Luminal B; 6 Her2; 30 Basal and 1 Normal, which encompasses the whole spectrum of PAM50. Thirty originators were also included and there are 8 Luminal A, 9 Luminal B, 2 Her2 and 11 Basal. With the matched 11 originators and the PDX models, 91% of their predicted subtypes are identical; 0.80 Cohen’s kappa was obtained, indicating high inter-rater agreement. We also described subsequent analysis with IHC data-based subtypes. For the 10 originators having IHC-based subtypes, 90% agreement was observed; for 24 PDX models with IHC data, 88% was observed. Of all the 180 PDX samples, 33 of the 43 PDX models (77%) have consistent predicted PAM50 molecular subtypes across different passages and lineages. Within the discordant samples, we observed cases such as a mixture of luminal B and Basal, which can be reasonably interpreted by AR positive signal from IHC. The discrepancy encourages further PDX subclassification from the Basal subtype. Conclusions: Using our high-throughput gene expression profiles from many patients and samples from patient derived models, we have demonstrated the feasibility of applying classic PAM50 classification algorithm, which was originally developed with microarray data, to be able to recognize the expression signals from our RNA-seq data. Overall, this study should set a primer for the identification of PDX-based subtypes, starting from breast cancer. Citation Format: Peter I. Wu, Lindsay Dutko, Shahanawaz Jiwani, Li Chen, Biswajit Das, Ting-Chia Chang, Yvonne A. Evrard, Chris A. Karlovich, Alyssa Chapman, Brandie Fullmer, Ashley Hayes, Ruth Thornton, Nikitha Nair, Kelly Benauer, Gloryvee Rivera, Thomas Forbes, John Carter, Suzanne Borgel, Tiffanie Miner, Chelsea McGlynn, Justine Mills, Shannon Uzelac, Tia Shearer, Lauren Hicks, Michelle Norris, Carley Border, Sergio Alcoser, Thomas Walsh, Michael Mullendore, Michelle Eugeni, Dianne Newton, Melinda G. Hollingshead, P. M. Williams, James H. Doroshow. Molecular subclassification of NCI PDMR breast cancer models using PAM50 gene expression signature [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2050.

Background: The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a large number of patient-derived xenograft (PDX) models from a diverse set of rare cancers. These models have been genomically characterized using whole-exome sequencing (WES) and RNAseq. The resource provides a unique opportunity to explore the genomic features of rare tumor models in NCI PDMR and to understand the oncogenic processes in pre-clinical models to identify biomarkers associated with therapeutic responses. Methods: Genomic characterization was done in 4-6 PDX samples across multiple passages and lineages from each model. As the samples exhibited a high level of genomic stability within each model, consensus mutation and copy number variation (CNV), microsatellite instability (MSI), genomic loss of heterozygosity (LOH), homologous recombination deficiency score (scarHRD), and mutational signature data were generated from WES. Fusions were identified from RNASeq data using Star-Fusion and FusionInspector. Gene set enrichment analysis was conducted from the gene expression data obtained from RNAseq. Results: 1) 233 PDX models have been developed and characterized from more than 45 different rare malignancies. Most frequent cancer types are different sarcomas (n=63), head & neck squamous cell carcinoma (n=61), and malignant fibrous histiocytoma (MFH) (n=11); 2) TP53 was the most frequently altered gene, mutated in 51% of models, followed by NOTCH1 (16%) and PIK3CA (11%). In terms of CNVs, ovarian epithelial cancer (OVT) showed relatively high chromosomal instability, while uterine endometrioid carcinoma (UEC) and synovial sarcoma (SYNS) had low instability; 3) MSI-H was observed in only 7 models. Esophageal adenocarcinoma (ESCA), OVT, and cervical squamous cell carcinoma (CESC) had high scarHRD and genomic LOH scores, while both scores were low in UEC and anal squamous cell carcinoma (ANSC). COSMIC v2 mutational signature 3 is significantly associated with a high scarHRD score (p-value < 0.01, Wilcoxon rank-sum test); 4) Characteristic fusions were observed in certain sarcoma models: SS18-SSX1 and ASPSCR1-TFE3 fusions were observed in SYNS and alveolar soft part sarcoma (ASPS) models respectively. EWSR1-FLI1 fusion was present in 2 out of 3 Ewing sarcoma (ES) models. 5) Gene set enrichment analysis from RNASeq data showed that epithelial-mesenchymal transition score could accurately distinguish carcinoma from sarcoma models, confirming the divergent gene expression programs. Conclusion: Comprehensive genomic characterization of NCI PDMR models generated from rare cancers solves an unmet need in the community. It will serve as a valuable resource for translational researchers interested in pre-clinical drug development and discovery. Citation Format: Li Chen, Rini Pauly, Ting-Chia Chang, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna Lee Fong, Amanda Peach, Shahanawaz Jiwani, Nastaran Neishaboori, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Corinne Camalier, Thomas Forbes, Michelle Gottholm-Ahalt, John Carter, Suzanne Borgel, Chelsea McGlynn, Candace Mallow, Emily Delaney, Tiffanie Miner, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 80.

NCI’s Patient-Derived Models Repository (NCI PDMR; pdmr.cancer.gov) has developed a variety of patient-derived models across most solid tumor histologies. These models are early passage, genetically characterized and associated with limited patient treatment history. As part of this effort, the NCI PDMR worked with the University of Nebraska Medical Center Rapid Autopsy Program and Johns Hopkins University Legacy Gift Rapid Autopsy Program to develop and optimize methods for collection, processing, and shipping of autopsy tumor material to maintain viability during overnight transit for use in patient-derived model development. These methods have been successfully transferred to two other participating rapid autopsy programs. To date, 412 autopsy tumor samples from 76 consented patients have been received for model development; 348 shipped overnight in media for next day implantation into NSG host mice and 64 cryopreserved prior to shipping for a comparative assessment of take-rate versus fresh tumor samples. On average 3-8 tumor samples, primary and metastatic, were collected post-mortem from the truncal region of each patient. Histologies include Pancreatic adenocarcinoma (n=43), Cholangiocarcinoma (n=6), Prostate adenocarcinoma (n=6), and 21 others with 1-2 patients/histology. The overall age range of enrolled patients was 5-88yo. The post-mortem cold ischemic time for collections ranged from 1.5 to 20 hours with a median of 3h (avg. 3.75h; outlier >11h removed). Collection methods were optimized to reduce contamination and increase viability of tumor tissues for successful PDX model generation. Of 348 fresh tumor samples collected to date, 69 PDX models from 33 patients have been generated (range 1-6 models/patient) and an additional 55 samples are being monitored for growth in passage 0. The largest public single-patient PDX model sets are for melanoma (899932-113-R, n=6) and two pancreatic adenocarcinomas (521955-158-R, n=6, 217524-143-R, n=4). Important methods for reducing contaminants in autopsy tumor material include sterilization of the surface of the body prior to opening, use of sterile fields, using separate sterile instruments for each collection site, rinsing the surface of the resected tumor tissue, and use of antibiotics in the collection media. The now established SOPs are publicly available on the NCI PDMR website (pdmr.cancer.gov/sops). We recommend incorporating as many of these methods as possible within the limitations of your individual site. Of the 69 models developed to date, 48 are publicly available from the NCI PDMR while the rest are undergoing quality control process prior to public release. Models developed from autopsy material provide a research tool to investigate tumor evolution, differences between primary and metastatic lesions, and assessment of differences in therapeutic response based on differences in the tumor biology. Citation Format: Yvonne A. Evrard, Michelle Eugeni, Michelle Ahalt-Gottholm, Carrie Bonomi, Suzanne Borgel, Thomas C. Caffrey, John Carter, Ting-Chia Chang, Li Chen, Kevin Cooper, Biswajit Das, Emily Delaney, Kelly Dougherty, Eleonora Duregon, Stephanie Ecker, Joe Geraghty, Marion Gibson, Lauren Hicks, Jenna Hull, Sharon Int Veldt, Shahanawaz Jiwani, Chris A. Karlovich, Jade Loewenstein, Candace Mallow, Chelsea McGlynn, Justine Mills, Tiffanie Miner, Jowaly Schneider, Tia Shearer, Savanna Styers, Shannon Uzelac, Paul Grandgenett, Michael Hollingsworth, Jody E. Hooper, P. Mickey Williams, Melinda Hollingshead, James H. Doroshow. Method development for generation of PDX models from rapid autopsy samples for the NCI patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3120.

Abstract Background: The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; pdmr.cancer.gov) is developing a variety of patient-derived xenograft (PDX) models for pre-clinical drug studies. All NCI PDMR models undergo quality control (QC) processes. Two unique QC challenges are: a) to assess genomic stability across PDX model passages; and b) to confirm the suitability of PDX-derived cancer associated fibroblasts (CAFs) as germline surrogates when blood is not available. Multiple bioinformatics QC assessments have been developed to measure the genomic fidelity in these PDX models using low-pass whole genome sequencing (LP-WGS) and in CAFs using whole exome sequencing (WES). Methods: LP-WGS was performed on 502 PDX samples from 38 models of rare cancer across passages 2 through 9 and WES was performed on 92 CAFs from 32 different histologies. In the QC workflow for estimating the genomic stability of passages within models, BBSplit was used for the assessment of human/mouse DNA content. CNVkit was utilized for copy number (CN) detection. The fraction of genome changed was calculated by comparing the copy numbers of each passage sample to the original patient sample. To evaluate purity of CAFs, three QC steps were constructed: a) plot of SNP variant allele frequency (ideogram); b) variant annotation using OncoKB (www.oncokb.org); c) percentage of genomic loss of heterozygosity (LOH), based on a set of ~800,000 heterozygous SNPs from a population-level genomic database (gnomAD) based on WES data. Results: PDX models showed genomic stability in CN profile when measured by LP-WGS. Human tumor DNA content remains stable ranging from 75-85% across different tiers of PDX passages from Donor +1 to Donor +6 and more. No models showed statistically significant evolution in CN profile, given the average 5 samples per model in each tier of passages. The QC workflow for CAFs generated five categories based on SNP ideograms, the presence/absence of oncogenic variants and LOH. Following observations were made: a) 72.5% CAFs were confirmed as matched diploid CAFs (category 1); b) 6.6% of CAFs were diploid and had >= 1 germline oncogenic variant - classified as category 2. CAFs in category 1&2 were suitable as germline surrogates; c) 12% of CAFs (category 3) showed putative polyploidy on SNP ideograms with no oncogenic variants and suitable for somatic variant calling; d) 8.8% of CAFs (category 4) had polyploidy and oncogenic variants present; e) LOH high CAF (category 5) - we identified a CAF with 42% LOH, later confirmed to be a tumor cell line by immunohistochemistry (IHC). Other CAFs (n=91) showed little variance, ranging from 0.6%-1.7% LOH. Conclusions: We developed standard QC workflows to evaluate genomic stability of PDX models during passaging and qualify CAFs as germline surrogates for pre-clinical study. Citation Format: Ting-Chia Chang, Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna J. Lee Fong, Amanda Peach, Brandie Fullmer, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Shahanawaz Jiwani, Nastaran Neishaboori, Tomas Forbes, Corinne Camalier, Luke Stockwin, Michael Mullendore, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, Mickey P. Williams, James H. Doroshow. Quality control workflows developed for the NCI Patient-Derived Models Repository using low pass whole genome sequencing and whole exome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1913.

Background: A major set of preclinical models derived from specimens acquired from rapid autopsy patients in the National Cancer Institute Patient-Derived Models Repository (NCI PDMR, https://pdmr.cancer.gov) were from pancreatic adenocarcinoma (PAAD) patients, with metastatic specimens originating from liver, colon, omentum, and lung. Genomic characterization of these preclinical models provides a unique opportunity to study tumor heterogeneity and subclonality associated with the metastatic process and potential treatment resistance. Methods: To date, 30 rapid autopsy patient-derived xenograft (PDX)/patient-derived cell (PDC)/patient-derived organoid (PDOrg ) models derived from pancreatic adenocarcinoma patients (n = 9) have been sequenced using whole-exome sequencing (WES) and RNASeq. Tumor heterogeneity between primary and metastatic sites was studied based on somatic mutation, copy number alteration (CNA) and gene expression data. A bioinformatics workflow was developed to stably infer and visualize the tumor subclonality by integrating the tools of PyClone, SCHISM, and TIMESCAPE, using somatic mutations and site-specific copy number data of multiple samples generated from PDX models in primary and metastatic sites. Results: Among 30 rapid autopsy preclinical models from primary and metastatic sites, liver is the most common metastatic site in PAAD (9/19=47%) compared to other sites. Driver mutations are conserved in all preclinical model specimens derived from a given patient. KRAS p.G12D is present in 28 PDX/PDC/PDOrg models as well as the corresponding patient specimens, and BRAF p.V600E is present in other preclinical models. The fraction of the genome affected by CNA remains stable within a PDX model across passages (n=18, mean=7.63%, sd=5.90%). However, we found that this increased when comparing PDX models derived from metastatic sites versus the primary site (n=16, mean=19.47%, sd=9.69%). This indicates the presence of tumor heterogeneity between metastatic and primary sites. Site-specific subclones were identified in PDX models from two patients (521955 and 485368) and a phylogenetic tree of primary and metastasis sites indicates that one liver metastasis had a unique seeding event compared to the other metastatic sites for both patients. Conclusion: Tumor heterogeneity and subclonality was observed in preclinical models generated from PAAD patients in the NCI PDMR. These models provide a unique resource for preclinical studies in tumor evolution, metastatic spread mediators, and drug resistance. Citation Format: Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Amanda Peach, Chapman Alyssa, Nikitha Nair, Anna L. Fong, Luis Romero, Ting-Chia Chang, Shahanawaz Jiwani, Lindsay Dutko, Kelly Benauer, Marianne Morton, Kelly Dougherty, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Study of tumor heterogeneity and subclonality in primary pancreatic and metastatic sites from rapid autopsy patients in PDMR [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3139.

Abstract There is an unmet need for preclinical models of rare cancers and rare disease sub-types. The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) is developing quality-controlled, early-passage, clinically-annotated patient-derived tumor xenografts (PDXs), in vitro tumor cell cultures (PDCs), cancer associated fibroblasts (CAFs), and patient-derived organoids (PDOrg) and has focused on addressing unmet needs in the preclinical model space including developing models from adult and pediatric patients with rare cancers. To date, NCI has created and molecularly characterized over 150 preclinical models of rare cancer including indications such as Hurthle cell carcinoma, osteosarcomas, Merkel cell carcinomas, salivary gland cancers, synovial sarcomas, and carcinosarcomas. Rare cancer models developed to date will be reviewed and their histopathologic and molecular characteristics compared to that reported in the clinical setting. A pipeline to identify fusion proteins in these rare cancers such as the Ewing sarcoma EWSR1-FLI1 fusion and NAB2-STAT6 fusions in solitary fibrous tumors (SFT) has been implemented. Four malignant peripheral nerve sheath tumors (MPNST) PDX models are available for researches; these models were developed from patients diagnosed between the ages of 37-68. At the time of model development, two patients were treatment naïve and two had prior radiotherapy. Two of the MPNST PDX models have NF1 oncogenic mutations, three have deep deletions in CDKN2A/B, and three have a mutation in either EED or SUZ12 consistent with the reported molecular characteristics of patients with MPNST. Also of clinical relevance, of two mesothelioma models available, one carries an NF2 driver mutation and the other BAP1 and LATS2 and a PDX model for Hurthle cell carcinoma has wide-spread loss of heterozygosity (LOH 80%). Models for other rare cancers are in development, including four cholangiocarcinoma PDXs with histopathologic confirmation that are currently being expanded for molecular characterization and distribution. Funded by NCI Contract No. HHSN261200800001E Citation Format: Cindy R. Timme, Sergio Y. Alcoser, Devynn Breen, John Carter, Ting-Chia Chang, Alice Chen, Li Chen, Kristen Cooley, Biswajit Das, Emily Delaney, Michelle A. Eugeni, Michelle M. Gottholm-Ahalt, Tara Grinnage-Polley, Jenna Hull, Chris Karlovich, Kimberly Klarmann, Shahanawaz Jiwani, Candace Mallow, Chelsea McGlynn, Justine Mills, Malorie Morris, Michael Mullendore, Dianne Newton, Tia Shearer, Jesse Stottlemyer, Shannon Uzelac, Thomas Walsh, P. Mickey Williams, Yvonne A. Evrard, Melinda G. Hollingshead, James H. Doroshow. Patient-derived models of rare cancers in the National Cancer Institute's patient-derived models repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3012.

e13506 Background: The National Cancer Institute has developed a repository of preclinical models [Patient-Derived Models Repository (NCI PDMR, https://pdmr.cancer.gov )] including patient derived xenografts (PDXs), organoids (PDOrgs) and in vitro tumor cultures (PDCs) from patients with solid tumor cancer histologies. A subset of these preclinical models is derived from post-mortem collections from rapid autopsies representing the end point in disease progression. Clinical annotations and genomic datasets associated with these models provide a unique opportunity to study tumor evolution, mechanistic insights into the metastatic process, and treatment resistance. Methods: To date, 43 PDXs, 21 PDCs, and 23 PDOrgs using rapid autopsy specimens from 8 primary and 35 metastatic sites of 18 patients have been developed by the Biological Testing Branch (DTP, DCTD, NCI Frederick, MD) for the PDMR. Whole exome (WES) and total transcriptome (RNASeq) data were processed to generate mutation, copy number alteration (CNA) and gene expression data. Multi-model lineage trees were reconstructed based on putative somatic variants for all the models derived from all patients. The fraction of the genome affected by CNA was compared both within and across PDX models. Results: Most of the rapid autopsy PDX models (32/43) are derived from pancreatic adenocarcinoma (PAAD) patients (13/18), with metastatic specimens originating from sites including liver, colon, omentum, and lung. Driver mutations are present in all preclinical model specimens derived from the same patient. For instance, KRAS p.G12D is present in all patient-derived model specimens derived from PAAD patient 521955. The fraction of the genome affected by CNA remains stable within a PDX model across passages (n = 24, mean = 6.39%, sd = 5.90%). However, we found that this increased when comparing PDX models derived from metastatic sites versus the primary site (n = 19, mean = 16.92%, sd = 10.46%). This indicates presence of tumor heterogeneity between metastatic and primary sites. The lineage tree for models from patient 521955 indicates that one liver metastasis has a unique seeding event compared to the other 4 metastatic sites. Unsupervised clustering analysis on gene expression data also confirms the observed tumor site relationships. Conclusions: Our data demonstrate the potential use of these preclinical models available from the NCI PDMR. These models provide a unique resource for preclinical studies in tumor evolution, metastatic spread mediators, and drug resistance.

Abstract Background: Acquired Uniparental Disomy (aUPD) is relatively common in cancer. Occurrence of aUPD is more frequent in some tumor histologies (e.g., serous ovarian, colorectal) and may be relevant for choice of therapy. The Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov) developed by The National Cancer Institute (NCI) includes patient-derived xenograft (PDX) models from multiple tumor histologies with different passages and lineages. The associated clinical annotation and genomic data make it possible to assess the prevalence of aUPD in the PDMR cohort and the stability of aUPD in different passages and lineages within a PDX model. Methods: High tumor purity in the PDX specimens (after removal of mouse reads representing the stroma) enabled highly accurate assessment of loss of heterozygosity (LOH). Variants called by GATK Haplotype caller from whole exome sequencing (WES) data were used to identify segments of homozygosity using BCFtools/RoH (runs of homozygosity). The RoH segments were then intersected with the bed file for chromosome arms to get %LOH at the arm level. If %LOH on a chromosome arm was >90%, we considered the sample to have aUPD at the arm level. WES was also used to look for associations between DNA damage repair (DDR) pathway alterations and aUPD. Results: We made the following observations: a) aUPD was observed most frequently in chr18q (75/427, 17.6%) and chr3p (69/427, 16%) of PDX models; b) aUPD was observed more frequently in certain tumor histologies, e.g., clear cell renal cell carcinoma (6/8), small cell lung cancer (3/4) and non-small cell lung cancer (25/38); c) extensive aUPD was observed in 4 PDMR models (>50% of evaluated chromosome arms in these models have aUPD); d) aUPD was not observed in some tumor histologies, i.e., synovial sarcoma, uterine endometrioid carcinoma; e) in the vast majority of PDMR models (>90%), aUPD is maintained faithfully across lineages and through multiple passaging; f) subclonal aUPD events were observed in some models across different lineages; g) significant enrichment of double strand DNA break repair (DSBR) pathway alterations was observed in PDMR models without aUPD (p=0.0007, Fisher's exact test) suggesting defects in DSBR are not associated with aUPD; and h) aUPD was rarely observed in MSI-high models (1/30) suggesting mutual exclusivity of mismatch repair (MMR) pathway defects and aUPD. Conclusion: We observed a relatively high frequency of UPD in the PDMR models (at least 1 arm of a chromosome). UPD was more frequently observed in specific chromosomal arms. The frequency of aUPD was higher in some tumor histologies and absent in others. aUPD was stably maintained across passages and lineages, although some heterogeneity was observed. Our data suggest aUPD is not associated with defects in DSBR and MMR pathways. Preclinical drug studies using NCI PDMR models may suggest appropriate therapeutic options for cancers with aUPD. Citation Format: Rajesh Patidar, Li Chen, Chris A. Karlovich, Biswajit Das, Yvonne A. Evrard, Tomas Vilimas, Justine N. McCutcheon, Amanda L. Peach, Nikitha V. Nair, Thomas D. Forbes, Brandie A. Fullmer, Anna J. Lee Fong, Luis E. Romero, Alyssa K. Chapman, Kelsey A. Conley, Robin D. Harrington, Shahanawaz S. Jiwani, Peng Wang, Michelle M. Gottholm Ahalt, Erin N. Cantu, Gloryvee Rivera, Lindsay M. Dutko, Kelly M. Benauer, Vishnuprabha R. Kannan, Suzanne D. Borgel, John P. Carter, Jesse M. Stottlemyer, Tiffanie L. Miner, Devynn R. Breen, Emily T. Delaney, Chelsea A. McGlynn, Candace N. Mallow, Marianne Radzyminski, Shannon N. Uzelac, Sergio Y. Alcoser, Tara L. Grinnage-Pulley, Michelle A. Eugeni, Dianne L. Newton, Melinda G. Hollingshead, Paul M. Williams, James H. Doroshow. Genomic landscape of acquired uniparental disomy in NCI PDMR patient derived xenograft models [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3554.

Abstract The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR) comprised of quality-controlled, early-passage, clinically-annotated patient-derived xenografts (PDXs) to serve as a resource for public-private partnerships and academic drug discovery efforts. These models are offered to the extramural community for research use (https://pdmr.cancer.gov/), along with clinical annotation and molecular information (whole exome sequence, RNASeq), which is available in a publicly accessible database. The PDMR was established by NCI at the Frederick National Laboratory for Cancer Research (FNLCR) in direct response to discussions with academia and industry; the oncology community's highest priority need was preclinical models that more faithfully reflect the patient's tumor and are associated with the patient's treatment history. NCI has focused on generating models to complement existing PDX collections and address unmet needs in the preclinical model space. The PDMR generates the majority of its PDXs by subcutaneous implantation except for those histologies having better success rates in either orthotopic or alternate implant sites. All SOPs and quality-control standards developed by the PDMR as well as those shared by collaborators are posted to a public web site that houses the PDMR database. In May 2017, the public website (https://pdmr.cancer.gov/) went live with its first 100 models from histologies including pancreatic, colorectal, renal, head and neck, and lung squamous cell cancers as well as melanoma and adult soft tissue sarcomas. In early 2018, the PDMR will begin releasing models from gynecological cancers, small cell lung cancer, chondro/osteo sarcomas, lung adenocarcinoma, and squamous cell skin and Merkel cell carcinomas. In addition, wherever available germline sequence and somatic variant calls will be added to the existing molecular characterization data for each model. NCI has also increased its focus on creating PDXs from racial and ethnic minorities through several funding opportunities. The overall goal of NCI is to create a long-term home for at least 1000 models such that sufficient biological and clinical diversity is represented to allow researchers to ask questions regarding the impact of tumor heterogeneity on target qualification or clinical response, whether PDXs more faithfully represent the human tumor for pharmacodynamic assay and predictive marker development, or if adequately powered preclinical PDX clinical trials can lead to better evaluation of therapies for future clinical use. Moving forward the PDMR plans to distribute in vitro, early-passage tumor cell cultures and cancer-associated fibroblasts as well as releasing PDX drug response data for a panel of FNA-approved therapeutic agents. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Michelle M. Gottholm Ahalt, Sergio . Y. Alcoser, Kaitlyn Arthur, Mariah Baldwin, Linda L. Blumenauer, Carrie Bonomi, Suzanne Borgel, Elizabeth Bradtke, Corinne Camalier, John Carter, Tiffanie Chase, Alice Chen, Lily Chen, Donna W. Coakley, Nicole E. Craig, Biswajit Das, Vivekananda Datta, Jordyn Davidson, Margaret R. DeFreytas, Emily Delaney, Michelle A. Eugeni, Raymond Divelbiss, Palmer Fliss, Thomas Forbes, Marion Gibson, Tara Grinnage-Pulley, Sierra Hoffman, Lilia Ileva, Paula Jacobs, Franklyn Jimenez, Joseph Kalen, Catherine Karangwa, Chris Karlovich, Candace Mallow, Chelsea McGlynn, Jenna E. Moyer, Michael Mullendore, Dianne L. Newton, Nimit Patel, Rajesh Patidar, Kevin Plater, Marianne Radzyminski, Lisa Riffle, Larry Rubinstein, Luke H. Stockwin, Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. The National Cancer Institute's patient-derived models repository (PDMR) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 986.

Background Molecular chaperone targeting has shown promise as a therapeutic approach in human cancers of various histologies and genetic backgrounds. The purine-scaffold inhibitor PU-H71 (NSC 750424), selective for Hsp90 in epichaperome networks, has demonstrated antitumor activity in multiple preclinical cancer models. The present study was a first in-human trial of PU-H71 aimed at establishing its safety and tolerability and characterizing its pharmacokinetic (PK) profile on a weekly administration schedule in human subjects with solid tumors refractory to standard treatments. Methods PU-H71 was administered intravenously over 1 h on days 1 and 8 of 21-day cycles in patients with refractory solid tumors. Dose escalation followed a modified accelerated design. Blood and urine were collected during cycles 1 and 2 for pharmacokinetics analysis. Results Seventeen patients were enrolled in this trial. Grade 2 and 3 adverse events were observed but no dose limiting toxicities occurred, thus the human maximum tolerated dose was not determined. The mean terminal half-life (T1/2) was 8.4 ± 3.6 h, with no dependency to dose level. A pathway for the metabolic disposal of PU-H71 in humans was derived from microsome studies. Fourteen patients were also evaluable for clinical response; 6 (35%) achieved a best response of stable disease for >2 cycles, with 2 patients remaining on study for 6 cycles. The study closed prematurely due to discontinuation of drug supply. Conclusions PU-H71 was well tolerated at the doses administered during this study (10 to 470 mg/m2/day), with no dose limiting toxicities.

Purpose PI3K/AKT/mTOR and RAS/RAF/MEK pathways are frequently dysregulated in colorectal cancer (CRC). We conducted a biomarker-driven trial of the combination of MK-2206, an allosteric AKT 1/2/3 inhibitor, and selumetinib, a MEK 1/2 inhibitor, in patients with CRC to evaluate inhibition of phosphorylated ERK (pERK) and AKT (pAKT) in paired tumor biopsies. Patients and Methods Adult patients with advanced CRC were enrolled in successive cohorts stratified by KRAS mutation status. Initially, 12 patients received oral MK-2206 90 mg weekly with oral selumetinib 75 mg daily in 28-day cycles. Following an interim analysis, the doses of MK-2206 and selumetinib were increased to 135 mg weekly and 100 mg daily, respectively. Paired tumor biopsies were evaluated for target modulation. Results Common toxicities were gastrointestinal, hepatic, dermatologic, and hematologic. Of 21 patients enrolled, there were no objective responses. Target modulation did not achieve the pre-specified criteria of dual 70 % inhibition of pERK and pAKT levels in paired tumor biopsies. Conclusion Despite strong scientific rationale and preclinical data, clinical activity was not observed. The desired level of target inhibition was not achieved. Overlapping toxicities limited the ability to dose escalate to achieve exposures likely needed for clinical activity, highlighting the challenges in developing optimal combinations of targeted agents.

BACKGROUND:Mutations in the KRAS gene predict for resistance to anti-epidermal growth factor receptor (EGFR) therapies, including cetuximab. Upregulation of vascular endothelial growth factor (VEGF)-A has been implicated in resistance to anti-EGFR treatment. Abrogation of the VEGF and RAS/RAF/MEK/ERK pathways has the potential to restore cetuximab sensitivity. PATIENTS AND METHODS:Adult patients with histologically documented, measurable, EGFR-expressing, KRAS-mutated metastatic colorectal cancer (mCRC) that had progressed after 5-fluorouracil-based regimens were treated with sorafenib 400 mg orally twice daily and intravenous cetuximab weekly in 28-day cycles. The primary endpoint was the response rate (complete response, partial response, and stable disease at 4 cycles). The secondary endpoints included plasma biomarker analysis of angiogenic cytokines and correlative imaging studies with dynamic contrast-enhanced magnetic resonance imaging and zirconium 89-panitumumab. RESULTS:Of the 30 patients enrolled, 26 were evaluable for response. Of the 26 patients evaluated, 4 had stable disease at 4 cycles and 1 had stable disease at 8 cycles. The median progression-free survival was 1.84 months. The common toxicities were rash, diarrhea, and liver enzyme elevations. Of the angiogenic cytokines evaluated, only the placental growth factor increased significantly with treatment (P < .0001). No pharmacodynamic parameters were associated with the treatment response. CONCLUSION:We report the results of a trial that combined cetuximab and sorafenib for the treatment of KRAS-mutated mCRC, with correlative imaging studies and pharmacodynamic angiogenic cytokine profiling as downstream markers of EGFR and VEGF receptor (VEGFR) signaling. No objective responses were observed. Additional development of biomarkers for patient selection is needed to evaluate combined EGFR and VEGFR blockade as a therapeutic option in KRAS-mutated CRC.

PURPOSE:A phase I dose escalation study was performed with systemically delivered lyso-thermosensitive liposomal doxorubicin (LTLD). The primary objectives were to determine the safe maximum tolerated dose (MTD), pharmacokinetic properties, and dose-limiting toxicity (DLT) of LTLD during this combination therapy.MATERIALS AND METHODS:Subjects eligible for percutaneous or surgical radiofrequency (RF) ablation with primary (n = 9) or metastatic (n = 15) tumors of the liver, with four or fewer lesions as large as 7 cm in diameter, were included. RF ablation was initiated 15 minutes after starting a 30-minute intravenous LTLD infusion. Dose levels between 20 mg/m(2) and 60 mg/m(2) were evaluated. Magnetic resonance imaging, positron emission tomography, and computed tomography were performed at predetermined intervals before and after treatment until evidence of recurrence was seen, administration of additional antitumor treatment was performed, or a total of 3 years had elapsed.RESULTS:DLT criteria were met at 60 mg/m(2), and the MTD was defined as 50 mg/m(2). RF ablation was performed during the peak of the plasma concentration-time curve in an effort to yield maximal drug deposition. LTLD produced reversible, dose-dependent neutropenia and leukopenia.CONCLUSIONS:LTLD can be safely administered systemically at the MTD (50 mg/m(2)) in combination with RF ablation, with limited and manageable toxicity. Further evaluation of this agent combined with RF ablation is warranted to determine its role in the management of liver tumors.